Abstract 1118: High-dimensional deconstruction of pancreatic cancer identifies co-occurring TME features associated with survival
Authors: Erik Storrs, Prathamesh Chati, Abul Usmani, Li Ding, Ryan Fields, Koushik Das, Aadel Chaudhuri
Journal: Cancer Research (2023)

Abstract Advances in single cell RNA sequencing (scRNA-seq) have provided the ability to describe individual cell profiles and query individual cell states, enabling a more in-depth analysis of the tumor microenvironment (TME) and tumor heterogeneity. We performed scRNA-seq of PDAC from standard-of-care endoscopic ultrasound guided fine needle biopsy (EUS-FNB) specimens at the time-of-diagnosis and from surgical samples obtained from tumor resections. In total, we acquired 32k cells across 25 independent PDAC samples for our in-house EUS-FNB cohort, and 12k cells from 6 independent PDAC samples for our in-house surgical cohort. To increase power, we then combined the in-house scRNA-seq data with three publicly available datasets, increasing our dataset to 80 samples. Cells were subsequently annotated based on a combination of known marker genes and gene set scores from the literature. Importantly, we partitioned malignant cells into Classical and Basal subtypes, CAFs into myofibroblast (myCAF) and inflammatory (iCAF) fibroblast, and TAMs into C1QC+, FCN1+, SPP1+, and proliferating TAMs based on similarity with previously published markers. We then determined the developmental status of the malignant and CAF subclusters with the CytoTRACE tool. We found that Basal malignant cells were less differentiated than their classical counterparts, agreeing with previous literature suggesting the aggressive basal subtype is more likely to undergo epithelial-mesenchymal transition (EMT). Interestingly, we also found that myCAFs are significantly less differentiated than iCAFs. We then extended our single cell expression profiles to 391 publicly available bulk expression samples with associated clinical metadata to find cell state patterns associated with patient survival. To this end, we modified the in-silico TME dissection tool EcoTyper and grouped significantly co-occurring cell states into ecotypes. Notably, one ecotype, termed PE3, showed consistently poor survival across all bulk RNA-seq datasets and harbored significant associations between Malignant - Basal, myCAF, and TAM - SPP1+ cell states, suggesting patients may benefit from treatment regimens that concurrently target TAM, CAF, and malignant cell dynamics in PDAC. In summary, we identified a novel TME community that revealed new connections between TME composition, developmental status, and patient survival that could lead to better upfront risk stratification and more personalized clinical decision-making. Citation Format: Erik Storrs, Prathamesh Chati, Abul Usmani, Li Ding, Ryan Fields, Koushik Das, Aadel Chaudhuri. High-dimensional deconstruction of pancreatic cancer identifies co-occurring TME features associated with survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1118.